model.py

import cv2
import numpy as np
import tensorflow as tf

def bone_frac(img):
    img = cv2.resize(img,(224,224))
    model = tf.keras.models.load_model("best_model.h5")
    result = model.predict(np.array([img]))
    op=""
    if result[0]<0.5:
        op="Normal"
    return op

# img = cv2.imread(r"C:\Users\kumar\Downloads\WhatsApp Image 2023-04-17 at 7.20.40 PM.jpeg")
# print(bone_frac(img))
# # bone_frac(img)